Welcome to CSAR
The University of Michigan was honored to host the Community Structure-Activity Resource (CSAR)!
This effort aimed to improve docking and scoring through participation of the entire scientific community. CSAR disseminated experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets were generated in house at the University of Michigan while others were collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry.
Computational drug design techniques are very successful at enriching hit rates when identifying sets of compounds for experimental testing. However, it is not possible to reliably rank nanomolar-level compounds over those with micromolar affinities. To improve our approaches, we need better datasets to train scoring functions and develop new docking algorithms.
CSAR was funded by a U01 grant from the National Institute of General Medical Sciences. The original RFA can be found at http://grants.nih.gov/grants/g uide/rfa-files/RFA-GM-08-008.html. Press releases about CSAR can be found at:
CSAR ran four exercises during its funding:
1) 2010 Benchmark (CSAR-HiQ set) Download Data
2) 2012 CSAR Exercise ((Cdk2 , Cdk2-CyclinA, LpxC) (Michigan), Urokinase (Abbott), Chk1 (Abbott), ERK2 (Vertex)) Download Data
3) 2013 Benchmark Exercise (Protein design in collaboration with David Baker, University of Washington) Download Data
4) 2014 Benchmark Exercise (fXa, Syk, TrmD donated by GlaxoSmithKline) Download Data
Other Data Deposited:
2011 Update to HiQ set. Download Data
CSAR decoys (Xiaoqin Zou, Missouri). Download Data
Kinase inactive set. Download Data
SAMPL1 Urokinase data (Abbott). Included with 2012 CSAR Exercise
DINGO (Tom Peat, CSIRO). Download Data
Neuraminidase (Roche), Malate Synthase (James Sacchettini, Texas A&M), PDF (GlaxoSmithKline), Physical property data Download Data
For questions, please contact BindingMOAD@umich.edu